ABSTRACT
In complex diseases, where many genes might be causally involved, individual loci influencing a quantitative trait are most likely to explain only a small proportion of the total variance. Consequently, there is a huge problem of lack of statistical power to detect such effects. Most linkage studies published to date consist only of a few hundred pedigrees, with only a small number of individuals each and, therefore, have little power to detect linkage of any but the “largest” quantitative trait loci (QTL). In order to enhance power, it is now common practice to retrospectively pool evidence for linkage from several different studies. However, in combining information from different studies, one should be aware of possible heterogeneity between studies. The aim of this chapter is to present statistical models for describing this heterogeneity, along with approaches to analyze heterogeneous data.
